@inproceedings{0bc898b64e2d4d86bad32b2b95e485b4,
title = "SVM-based learning method for improving colour adjustment in automotive basecoat manufacturing",
abstract = "A new iterative method based on Support Vector Machines to perform automated colour adjustment processing in the automotive industry is proposed in this paper. The iterative methodology relies on a SVM trained with patterns provided by expert colourists and an actions' generator module. The SVM algorithm enables selecting the most adequate action in each step of an iterated feed-forward loop until the final state satisfies colourimetric bounding conditions. Both encouraging results obtained and the significant reduction of non-conformance costs, justify further industrial efforts to develop an automated software tool in this and similar industrial processes.",
author = "Ruiz, {Francisco J.} and N{\'u}ria Agell and Cecilio Angulo",
year = "2009",
language = "English",
isbn = "2930307099",
series = "ESANN 2009 Proceedings, 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning",
pages = "343--348",
booktitle = "ESANN 2009 Proceedings, 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning",
note = "17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2009 ; Conference date: 22-04-2009 Through 24-04-2009",
}